ENTROPY FLOW CHARACTERISTICS ANALYSIS OF TYPHOON MATSA (0509)

The evolution of Typhoon Matsa (0509) is examined in terms of entropy flow through an entropy balance equation derived from the Gibbs relation, according to the second law of thermodynamics. The entropy flows in the various significant stages of (genesis, development and decaying) during its evolution are diagnosed based on the outputs of the PSU/NCAR mesoscale model (known as MM5). The results show that: (1) the vertical spatial distribution of entropy flow for Matsa is characterized by a predominantly negative entropy flow in a large portion of the troposphere and a positive flow in the upper levels; (2) the fields of entropy flows at the middle troposphere (500 hPa) show that the growth of the typhoon is greatly dependent on the negative entropy flows from its surroundings; and (3) the simulated centres of heavy rainfall associated with the typhoon match well with the zones of large negative entropy flows, suggesting that they may be a significant indicator for severe weather events.

THE EFFECT OF THE NEGATIVE ENTROPY FLOW ON THE ORGANIZATION OF ATMOSPHERIC DISSIPATIVE STRUCTURES IN NON-EQUILIBRIUM CONDITIONS

The entropy balance equation that describes the entropy budget of atmospheric systems is derived from the Gibbs relation.The distribution of the entropy flows of a west-Pacific typhoon and a Bengal-Bay cyclone is calculated and thus the dissipativity of the atmospheric systems is revealed.

Abnormal Crowd Behavior Detection Based on the Entropy of Optical Flow

To improve the detection accuracy and robustness of crowd anomaly detection,especially crowd emergency evacuation detection,the abnormal crowd behavior detection method is proposed.This method is based on the improved statistical global optical flow entropy which can better describe the degree of chaos of crowd.First,the optical flow field is extracted from the video sequences and a 2D optical flow histogram is gained.Then,the improved optical flow entropy,combining information theory with statistical physics is calculated from 2D optical flow histograms.Finally,the anomaly can be detected according to the abnormality judgment formula.The experimental results show that the detection accuracy achieved over 95%in three public video datasets,which indicates that the proposed algorithm outperforms other state-of-the-art algorithms.

A Novel Location Method for Interline Power Flow Controllers Based on Entropy Theory

As one of the new generation flexible AC transmission systems(FACTS)devices,the interline power flow controller(IPFC)has the significant advantage of simultaneously regulating the power flow of multiple lines.Nevertheless,how to choose the appropriate location for the IPFC converters has not been discussed thoroughly.To solve this problem,this paper proposes a novel location method for IPFC using entropy theory.To clarify IPFC’s impact on system power flow,its operation mechanism and control strategies of different types of serial converters are discussed.Subsequently,to clarify the system power flow characteristic suitable for device location analysis,the entropy concept is introduced.In this process,the power flow distribution entropy index is used as an optimization index.Using this index as a foundation,the power flow transfer entropy index is also generated and proposed for the IPFC location determination study.Finally,electromechanical electromagnetic hybrid simulations based on ADPSS are implemented for validation.These are tested in a practical power grid with over 800 nodes.A modular multilevel converter(MMC)-based IPFC electromagnetic model is also established for precise verification.The results show that the proposed method can quickly and efficiently complete optimized IPFC location and support IPFC to determine an optimal adjustment in the N-1 fault cases.

Optimal allocation of multi-type FACTS devices in power systems based on power flow entropy

Flexible AC transmission systems(FACTS)devices can effectively optimize the distribution of power flow.Power flow entropy can be applied as a measure of load distribution.In this paper,a method is proposed to optimize the distribution of power flow with the coordination of multi-type FACTS devices and establishes the corresponding mathematical models.The modified group searcher optimization(GSO)algorithm is proposed,in which the angle search is combined with chaotic search model to avoid jumping into local optimization.Compared with the different optimal allocation of multi-FACTS devices,the optimal allocation of multi-FACTS devices is achieved under the economic constraints.The locations obtained by this method can achieve the purpose of balancing power flow and enhancing the system performances.The simulations are demonstrated in an IEEE 118-bus power system with two classical types of FACTS,namely static var compensator(SVC)and thyristor controlled series Compensator(TCSC).The simulation results show that the proposed method is feasible and effective.

Numerical investigation of entropy generation and heat transfer of pulsating flow in a horizontal channel with an open cavity

In this study, the entropy generation and the heat transfer of pulsating air flow in a horizontal channel with an open cavity heated from below with uniform temperature distribution are numerically investigated. A numerical method based on finite volume method is used to discretize the governing equations. At the inlet of the channel, pulsating velocity is imposed for a range of Strouhal numbers Stpfrom 0 to 1 and amplitude Apfrom 0 to 0.5. The effects of the governing parameters, such as frequency and amplitude of the pulsation, Richardson number, Ri, and aspect ratio of the cavity, L/H, on the flow field, temperature distribution, average Nusselt number and average entropy generation, are numerically analyzed. The results indicate that the heat transfer and entropy generation are strongly affected by the frequency and amplitude of the pulsation and this depends on the Richardson number and aspect ratio of the cavity. The pulsation is more effective with the aspect ratio of the cavity L/H= 1.5 in terms of heat transfer enhancement and entropy generation minimization.

A Brief Review of High Entropy Alloys and Serration Behavior and Flow Units

Multicomponent alloys with high entropy of mixing,e.g.,high entropy alloys（HEAs）and/or multiprincipal-element alloys（MEAs）,are attracting increasing attentions,because the materials with novel properties are being developed,based on the design strategy of the equiatomic ratio,multicomponent,and high entropy of mixing in their liquid or random solution state.Recently,HEAs with the ultrahigh strength and fracture toughness,excellent magnetic properties,high fatigue,wear and corrosion resistance,great phase stability/high resistance to heat-softening behavior,sluggish diffusion effects,and potential superconductivity,etc.,were developed.The HEAs can even have very high irradiation resistance and may have some self-healing effects,and can potentially be used as the first wall and nuclear fuel cladding materials.Serration behaviors and flow units are powerful methods to understand the plastic deformation or fracture of materials.The methods have been successfully used to study the plasticity of amorphous alloys（also bulk metallic glasses,BMGs）.The flow units are proposed as：free volumes,shear transition zones（STZs）,tension-transition zones（TTZs）,liquid-like regions,soft regions or soft spots,etc.The flow units in the crystalline alloys are usually dislocations,which may interact with the solute atoms,interstitial types,or substitution types.Moreover,the flow units often change with the testing temperatures and loading strain rates,e.g.,at the low temperature and high strain rate,plastic deformation will be carried out by the flow unit of twinning,and at high temperatures,the grain boundary will be the weak area,and play as the flow unit.The serration shapes are related to the types of flow units,and the serration behavior can be analyzed using the power law and modified power law.

Entropy Generation Analysis in Convective Ferromagnetic Nano Blood Flow Through a Composite Stenosed Arteries with Permeable Wall

The study of heat transfer is of significant importance in many biological and biomedical industry problems.This investigation comprises of the study of entropy generation analysis of the blood flow in the arteries with permeable walls. The convection through the flow is studied with compliments to the entropy generation. Governing problem is formulized and solved for low Reynold's number and long wavelength approximations. Exact analytical solutions have been obtained and are analyzed graphically. It is seen that temperature for pure water is lower as compared to the copper water. It gains magnitude with an increase in the slip parameter.

An investigation into flow mode transition and pressure fluctuations for fluidized dense-phase pneumatic conveying of fine powders

This paper presents the results of an ongoing investigation into the fluctuations of pressure signals due to solids-gas flows for dense-phase pneumatic conveying of fine powders. Pressure signals were obtained from pressure transducers installed along different locations of a pipeline for the fluidized dense-phase pneumatic conveying of fly ash （median particle diameter 30μm; particle density 2300 kg/m^3; loose- poured bulk density 700 kg/m^3） and white powder （median particle diameter 55 p.m; particle density 1600 kg/m^3 ; loose-poured bulk density 620 kg/m^3） from dilute to fluidized dense-phase. Standard deviation and Shannon entropy were employed to investigate the pressure signal fluctuations. It was found that there is an increase in the values of Shannon entropy and standard deviation for both of the prod- ucts along the flow direction through the straight pipe sections. However, both the Shannon entropy and standard deviation values tend to decrease after the flow through bend（s）, This result could be attributed to the deceleration of particles while flowing through the bends, resulting in dampened particle fluctua- tion and turbulence. Lower values of Shannon entropy in the early parts of the pipeline could be due to the non-suspension nature of flow （dense-phase）, i.e., there is a higher probability that the particles are concentrated toward the bottom of pipe, compared with dilute-phase or suspension flow （high velocity）, where the particles could be expected to be distributed homogenously throughout the pipe bore （as the flow is in suspension）. Changes in straight-pipe pneumatic conveying characteristics along the flow direction also indicate a change in the flow regime along the flow.

Experimental investigation into transient pressure pulses during pneumatic conveying of fine powders using Shannon entropy

This paper presents the results of an ongoing investigation into transient pressure pulses using Shan- non entropy. Pressure fluctuations （produced by gas-solid two-phase flow during fluidized dense-phase conveying） are recorded by pressure transducers installed at strategic locations along a pipeline. This work validates previous work on identifying the flow mode from pressure signals （Mittal, Mallick, ＆ Wypych, 2014）. Two different powders, namely fly ash （median particle diameter 45 μm, particle den- sity 1950 kg/m3. loosely poured bulk density 950 kg/m3） and cement （median particle diameter 15 p,m, particle density 3060 kg/m3, loosely poured bulk density 1070 kg/m3）, are conveyed through different pipelines （51 mm I.D. × 70 m length and 63 mm I.D. × 24 m length）. The transient nature of pressure fluc- tuations （instead of steady-state behavior） is considered in investigating flow characteristics. Shannon entropy is found to increase along straight pipe sections for both solids and both pipelines. However, Shannon entropy decreases after a bend. A comparison of Shannon entropy among different ranges of superficial air velocity reveals that high Shannon entropy corresponds to very low velocities （i.e. 3-5 m/s） and very high velocities （i.e. 11-14 m/s） while low Shannon entropy corresponds to mid-range velocities （i.e. 6-8 m/s）.

c-CSN:Single-cell RNA Sequencing Data Analysis by Conditional Cell-specific Network

t The rapid advancement of single-cell technologies has shed new light on the complex mechanisms of cellular heterogeneity.However,compared to bulk RNA sequencing(RNA-seq),single-cell RNA-seq(scRNA-seq)suffers from higher noise and lower coverage,which brings new computational difficulties.Based on statistical independence,cell-specific network(CSN)is able to quantify the overall associations between genes for each cell,yet suffering from a problem of overestimation related to indirect effects.To overcome this problem,we propose the c-CSN method,which can construct the conditional cell-specific network(CCSN)for each cell.c-CSN method can measure the direct associations between genes by eliminating the indirect associations.c-CSN can be used for cell clustering and dimension reduction on a network basis of single cells.Intuitively,each CCSN can be viewed as the transformation from less“reliable”gene expression to more“reliable”gene–gene associations in a cell.Based on CCSN,we further design network flow entropy(NFE)to estimate the differentiation potency of a single cell.A number of scRNA-seq datasets were used to demonstrate the advantages of our approach.1)One direct association network is generated for one cell.2)Most existing scRNA-seq methods designed for gene expression matrices are also applicable to c-CSN-transformed degree matrices.3)CCSN-based NFE helps resolving the direction of differentiation trajectories by quantifying the potency of each cell.c-CSN is publicly available at https://github.com/LinLi-0909/c-CSN.

Dynamic statistical information theory

In recent years we extended Shannon static statistical information theory to dynamic processes and established a Shannon dynamic statistical information theory, whose core is the evolution law of dynamic entropy and dynamic information. We also proposed a corresponding Boltzmman dynamic statistical information theory. Based on the fact that the state variable evolution equation of respective dynamic systems, i.e. Fok- ker-Planck equation and Liouville diffusion equation can be regarded as their information symbol evolution equation, we derived the nonlinear evolution equations of Shannon dy- namic entropy density and dynamic information density and the nonlinear evolution equa- tions of Boltzmann dynamic entropy density and dynamic information density, that de- scribe respectively the evolution law of dynamic entropy and dynamic information. The evolution equations of these two kinds of dynamic entropies and dynamic informations show in unison that the time rate of change of dynamic entropy densities is caused by their drift, diffusion and production in state variable space inside the systems and coordinate space in the transmission processes; and that the time rate of change of dynamic infor- mation densities originates from their drift, diffusion and dissipation in state variable space inside the systems and coordinate space in the transmission processes. Entropy and in- formation have been combined with the state and its law of motion of the systems. Fur- thermore we presented the formulas of two kinds of entropy production rates and infor- mation dissipation rates, the expressions of two kinds of drift information flows and diffu- sion information flows. We proved that two kinds of information dissipation rates (or the decrease rates of the total information) were equal to their corresponding entropy produc- tion rates (or the increase rates of the total entropy) in the same dynamic system. We obtained the formulas of two kinds of dynamic mutual informations and dynamic channel capacities reflecting the dynamic dissipation characteristics in the transmission processes, which change into their maximum—the present static mutual information and static channel capacity under the limit case where the proportion of channel length to informa- tion transmission rate approaches to zero. All these unified and rigorous theoretical for- mulas and results are derived from the evolution equations of dynamic information and dynamic entropy without adding any extra assumption. In this review, we give an overview on the above main ideas, methods and results, and discuss the similarity and difference between two kinds of dynamic statistical information theories.

Serration and Noise Behavior in Advanced Materials

The Chinese Materials Research Society（C-MRS）Conference（2015）was held in the Guizhou Park Hotel International Conference Center,Guiyang,China,from July 10-14,2015.This conference consists of 30symposia,including 4international symposia.As one of 4international symposia,＂Serration and noise behavior in advanced materials＂